Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
dARK ID: | ark:/26339/001300000gqsd |
Texto Completo: | http://repositorio.ufsm.br/handle/1/23719 |
Resumo: | The objective of this research was to develop and validate a hardware device with temperature, relative humidity and CO2 sensors for indirect monitoring of grain mass quality. All experimental steps were carried out at the Post-Harvest and Electrical Engineering Laboratory of the Federal University of Santa Maria, Campus Cachoeira do Sul. Chapter I comprised the construction / development and validation stages of the equipment. In the first part, a probe for conditioning the sensors was tested, in which the hole diameter and perforation height were changed. In the second part, mathematical modeling was used, evaluating different equilibrium moisture equations. In the last part of Chapter I, we sought to validate the harvest in soybeans with different qualities. With the results, it was observed that a probe with a bore diameter of 6.5 mm and a perforation height of 235 mm had a faster response for stabilizing the readings. The quantification of CO2 made it possible to carry out correlations with the quality of grain mass. Water contents of 10 and 13% had lower levels of carbon dioxide, while grains with water contents of 25% achieved a CO2 concentration of 5000 ppm. In evaluating the moisture balance of the intergranular air in the grain mass, it was observed that the Sigma Copace equation was the one that best fit the results. The quality results obtained by the germination and electrical conductivity tests in the grains were correlated with the concentration of carbon dioxide obtained in the grain mass. Grains with germination percentage of 78% and electrical conductivity of 126.75 μS cm-¹ had low CO2 values. As for grains with low germination values (6%) and high electrical conductivity values of 426.54 μS.cm-1, the concentration of carbon dioxide was 3500 ppm. In Chapter II, transport conditions were simulated, using grains with water contents of 11, 14 and 18%. Grains were monitored at three heights in three layers in the conveyor system. The results obtained have direct application to producers and grain storage and processing industries, in the monitoring and prediction of grain quality, as well as in storage and transport logistics. The water content associated with time were the factors with the greatest influence on the quality of transported grains. Displacement time is the determining factor for controlling the quality of grains during transport. Soybeans harvested from crops with a water content between 14 and 18% must not exceed 120 minutes of transport time to maintain quality. It is recommended that the transport time of grains shipped from storage units to processing industries, with a water content between 11 and 14%, does not exceed 840 minutes. The monitoring of indirect quality measurement variables associated with the application of Machine Learning models satisfactorily predicted the physical quality of the grain mass, along the transport time, for the different conditions tested. |
id |
UFSM_45ea25b4456d8ff42275dc59fbe33b69 |
---|---|
oai_identifier_str |
oai:repositorio.ufsm.br:1/23719 |
network_acronym_str |
UFSM |
network_name_str |
Manancial - Repositório Digital da UFSM |
repository_id_str |
|
spelling |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviárioDevelopment and validation of a device for monitoring the quality of soybean mass in road transportDióxido de carbonoArmazenamentoUmidade de equilíbrio higroscópicoPós-colheitaSojaCarbon dioxideHygroscopic equilibrium humidityPost-harvestSoybeanCNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLAThe objective of this research was to develop and validate a hardware device with temperature, relative humidity and CO2 sensors for indirect monitoring of grain mass quality. All experimental steps were carried out at the Post-Harvest and Electrical Engineering Laboratory of the Federal University of Santa Maria, Campus Cachoeira do Sul. Chapter I comprised the construction / development and validation stages of the equipment. In the first part, a probe for conditioning the sensors was tested, in which the hole diameter and perforation height were changed. In the second part, mathematical modeling was used, evaluating different equilibrium moisture equations. In the last part of Chapter I, we sought to validate the harvest in soybeans with different qualities. With the results, it was observed that a probe with a bore diameter of 6.5 mm and a perforation height of 235 mm had a faster response for stabilizing the readings. The quantification of CO2 made it possible to carry out correlations with the quality of grain mass. Water contents of 10 and 13% had lower levels of carbon dioxide, while grains with water contents of 25% achieved a CO2 concentration of 5000 ppm. In evaluating the moisture balance of the intergranular air in the grain mass, it was observed that the Sigma Copace equation was the one that best fit the results. The quality results obtained by the germination and electrical conductivity tests in the grains were correlated with the concentration of carbon dioxide obtained in the grain mass. Grains with germination percentage of 78% and electrical conductivity of 126.75 μS cm-¹ had low CO2 values. As for grains with low germination values (6%) and high electrical conductivity values of 426.54 μS.cm-1, the concentration of carbon dioxide was 3500 ppm. In Chapter II, transport conditions were simulated, using grains with water contents of 11, 14 and 18%. Grains were monitored at three heights in three layers in the conveyor system. The results obtained have direct application to producers and grain storage and processing industries, in the monitoring and prediction of grain quality, as well as in storage and transport logistics. The water content associated with time were the factors with the greatest influence on the quality of transported grains. Displacement time is the determining factor for controlling the quality of grains during transport. Soybeans harvested from crops with a water content between 14 and 18% must not exceed 120 minutes of transport time to maintain quality. It is recommended that the transport time of grains shipped from storage units to processing industries, with a water content between 11 and 14%, does not exceed 840 minutes. The monitoring of indirect quality measurement variables associated with the application of Machine Learning models satisfactorily predicted the physical quality of the grain mass, along the transport time, for the different conditions tested.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESO objetivo desta pesquisa foi desenvolver e validar um dispositivo hardware com sensores de temperatura, umidade relativa e CO2 para monitoramento indireto da qualidade da massa de grãos. Todas as etapas experimentais foram realizadas no Laboratório de Pós-Colheita e Engenharia Elétrica da Universidade Federal de Santa Maria, Campus Cachoeira do Sul. O Capitulo I compreendeu etapas de construção/desenvolvimento e validação do equipamento. Na primeira parte testou-se uma sonda para acondionamento dos sensores na qual foi empregado diferentes diâmetros de furos e altura de perfuração. Na segunda parte, foi empregada a modelagem matemática, sendo avaliado diferentes equações de umidade de equilíbrio. Na última parte do Capítulo I, buscou-se validar o equipamento inserindo-o em grãos de soja com qualidades distintas. Com os resultados, foi observado que a sonda com furo de diâmetro de 6,5 mm e altura de perfuração de 235 mm teve uma resposta mais rápida para a estabilização das leituras. A quantificação de CO2 possibilitou realizar correlações com a qualidade da massa de grãos. Os teores de água de 10 e 13% obtiveram níveis mais baixos de dióxido de carbono, enquanto os grãos com teores de água de 25% alcançaram uma concentração de CO2 de 5000 ppm. Na avaliação da umidade de equilíbrio higroscópico do ar intergranular da massa de grãos, observou - se que a equação Sigma Copace foi a que melhor ajustou aos resultados. Os resultados de qualidade obtidos pelos testes de germinação e de condutividade elétrica nos grãos se correlacionaram com a concentração de dióxido de carbono obtida na massa de grãos. Os grãos com percentual germinativo de 78% e condutividade elétrica de 126,75 μS cm-¹ apresentaram valores baixos de CO2. Já os grãos com baixos valores de germinação (6%) e altos valores de condutividade elétrica de 426,54 μS.cm-1, a concentração de dióxido de carbon foi de 3500 ppm. No Capítulo II foi simulado condições de transporte, por meio de grãos com teores de água de 11, 14 e 18%. Os grãos foram monitorados em três alturas em três camada no sistema de transporte. Os resultados obtidos têm aplicação direta aos produtores e indústrias de armazenamento e processamento de grãos, no monitoramento e previsão da qualidade dos grãos, bem como na logística de armazenamento e transporte. O teor de água associado ao tempo foram os fatores com maior influência na qualidade dos grãos transportados. O tempo de deslocamento é o fator determinante para o controle da qualidade dos grãos durante o transporte. Lotes de soja colhidos de lavouras com teor de água entre 14 e 18% não devem exceder 120 minutos de tempo de transporte para manter a qualidade. Recomenda-se que o tempo de transporte dos grãos expedidos das unidades de armazenamento para as indústrias de processamento, com teor de água entre 11 e 14%, não ultrapasse 840 minutos. O monitoramento de variáveis indiretas de medição de qualidade associadas à aplicação de modelos de Aprendizado de Máquina previu satisfatoriamente a qualidade física da massa de grãos, ao longo do tempo de transporte, para as diferentes condições testadas.Universidade Federal de Santa MariaBrasilEngenharia AgrícolaUFSMPrograma de Pós-Graduação em Engenharia AgrícolaCentro de Ciências RuraisCoradi, Paulo Carterihttp://lattes.cnpq.br/5926614370728576Carvalho , Ivan RicardoBrackmann, AuriSantos, Joseane Erbice dosTres, Marcus ViníciusParaginski, Ricardo TadeuJaques, Lanes Beatriz Acosta2022-02-23T12:21:59Z2022-02-23T12:21:59Z2021-11-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/23719ark:/26339/001300000gqsdporAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2022-03-28T14:13:21Zoai:repositorio.ufsm.br:1/23719Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2022-03-28T14:13:21Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário Development and validation of a device for monitoring the quality of soybean mass in road transport |
title |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
spellingShingle |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário Jaques, Lanes Beatriz Acosta Dióxido de carbono Armazenamento Umidade de equilíbrio higroscópico Pós-colheita Soja Carbon dioxide Hygroscopic equilibrium humidity Post-harvest Soybean CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
title_short |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
title_full |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
title_fullStr |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
title_full_unstemmed |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
title_sort |
Desenvolvimento e validação de um dispositivo para monitoramento da qualidade da massa de grãos de soja no transporte rodoviário |
author |
Jaques, Lanes Beatriz Acosta |
author_facet |
Jaques, Lanes Beatriz Acosta |
author_role |
author |
dc.contributor.none.fl_str_mv |
Coradi, Paulo Carteri http://lattes.cnpq.br/5926614370728576 Carvalho , Ivan Ricardo Brackmann, Auri Santos, Joseane Erbice dos Tres, Marcus Vinícius Paraginski, Ricardo Tadeu |
dc.contributor.author.fl_str_mv |
Jaques, Lanes Beatriz Acosta |
dc.subject.por.fl_str_mv |
Dióxido de carbono Armazenamento Umidade de equilíbrio higroscópico Pós-colheita Soja Carbon dioxide Hygroscopic equilibrium humidity Post-harvest Soybean CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
topic |
Dióxido de carbono Armazenamento Umidade de equilíbrio higroscópico Pós-colheita Soja Carbon dioxide Hygroscopic equilibrium humidity Post-harvest Soybean CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA |
description |
The objective of this research was to develop and validate a hardware device with temperature, relative humidity and CO2 sensors for indirect monitoring of grain mass quality. All experimental steps were carried out at the Post-Harvest and Electrical Engineering Laboratory of the Federal University of Santa Maria, Campus Cachoeira do Sul. Chapter I comprised the construction / development and validation stages of the equipment. In the first part, a probe for conditioning the sensors was tested, in which the hole diameter and perforation height were changed. In the second part, mathematical modeling was used, evaluating different equilibrium moisture equations. In the last part of Chapter I, we sought to validate the harvest in soybeans with different qualities. With the results, it was observed that a probe with a bore diameter of 6.5 mm and a perforation height of 235 mm had a faster response for stabilizing the readings. The quantification of CO2 made it possible to carry out correlations with the quality of grain mass. Water contents of 10 and 13% had lower levels of carbon dioxide, while grains with water contents of 25% achieved a CO2 concentration of 5000 ppm. In evaluating the moisture balance of the intergranular air in the grain mass, it was observed that the Sigma Copace equation was the one that best fit the results. The quality results obtained by the germination and electrical conductivity tests in the grains were correlated with the concentration of carbon dioxide obtained in the grain mass. Grains with germination percentage of 78% and electrical conductivity of 126.75 μS cm-¹ had low CO2 values. As for grains with low germination values (6%) and high electrical conductivity values of 426.54 μS.cm-1, the concentration of carbon dioxide was 3500 ppm. In Chapter II, transport conditions were simulated, using grains with water contents of 11, 14 and 18%. Grains were monitored at three heights in three layers in the conveyor system. The results obtained have direct application to producers and grain storage and processing industries, in the monitoring and prediction of grain quality, as well as in storage and transport logistics. The water content associated with time were the factors with the greatest influence on the quality of transported grains. Displacement time is the determining factor for controlling the quality of grains during transport. Soybeans harvested from crops with a water content between 14 and 18% must not exceed 120 minutes of transport time to maintain quality. It is recommended that the transport time of grains shipped from storage units to processing industries, with a water content between 11 and 14%, does not exceed 840 minutes. The monitoring of indirect quality measurement variables associated with the application of Machine Learning models satisfactorily predicted the physical quality of the grain mass, along the transport time, for the different conditions tested. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-11-16 2022-02-23T12:21:59Z 2022-02-23T12:21:59Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/23719 |
dc.identifier.dark.fl_str_mv |
ark:/26339/001300000gqsd |
url |
http://repositorio.ufsm.br/handle/1/23719 |
identifier_str_mv |
ark:/26339/001300000gqsd |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia Agrícola UFSM Programa de Pós-Graduação em Engenharia Agrícola Centro de Ciências Rurais |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia Agrícola UFSM Programa de Pós-Graduação em Engenharia Agrícola Centro de Ciências Rurais |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
_version_ |
1815172340882866176 |